Digital radio systems

ABSTRACT

Apparatus comprising a pre-filter rake architecture with various features designed to, in at least some circumstances, to lessen the data processing burden associated with the architecture. In one embodiment, the pre-filter aspect can be disabled.

BACKGROUND

In a typical radio system (see FIG. 1), information is modulated onto aradio carrier by a transmitter. This signal then travels via an unknownand changing environment to the receiver. The ability to remove theeffects of the environment from the signal is often key to theperformance of a receiver.

The transmitter 101 passes information bits through a block adding errorprotection coding 102 and then through a modulation block 103 whichmodulates the coded information onto a radio carrier. As part of themodulation, known symbols may be added to assist with radio channelestimation in the receiver.

Once transmitted, the radio signal then passes through the radio channel104 before reception 108. This radio channel frequently gives rise toInter-Symbol Interference (ISI) which must then be removed by thereceiver to ensure correct reception. Before being processed by thereceiver blocks, the signal also acquires both interference and noise.The interference arises from other users of the spectrum whilst thenoise is thermal noise from the environment. Additional noise is thenadded as the signal passes through the Rx front end 105.

The receiver 108 converts the analogue radio signal to a digital baseband signal in the Rx front-end 105. The signal is then passed throughthe demodulation block 106. This serves to estimate the transmittedcoded-bits in the presence of the ISI, interference and noise added bythe radio channel and the Rx front end. The signal is then decoded 107to yield the final received information bits.

The quality of service experienced by the user as well as the overallcapacity of the system depends largely on the selected implementation ofthe demodulation unit. For W-CDMA systems, it is typical to use a Rakearchitecture in the receiver (CDMA—Principles of Spread SpectrumCommunication, Andrew J. Viterbi, Addison-Wesley Wireless CommunicationsSeries). The Rake receiver combines the contributions from the differentpaths in the propagation channel in order to generate samples to beprocessed by the channel decoder. The Rake receiver is therefore able toexploit the diversity provided by the propagation channel. However, thedecisions generated by the Rake receiver suffer from an increase innoise level due to ISI.

High-Speed Downlink Packet Access (HSDPA) is an evolution of the Release99 version of the 3GPP standard aimed at providing improved userexperience through increased data rates and reduced end-to-end latency.These improvements are delivered through a combination of IncrementalRedundancy (IR) and the use of higher-order modulation schemes. HSDPAextends the capabilities of 3GPP by introducing the use of the 16QAMmodulation for the data bearing channels. The 16QAM modulation is morespectrally efficient than the QPSK modulation used in 3G. However, it isalso more sensitive to impairments introduced in the transmission link.Hence, in order to fully exploit the benefits of the new featuresintroduced in HSDPA, it is important to select an implementation of thedemodulation unit which is resistant to noise and interference.

Recently, new receiver architectures have been introduced where thedemodulation accuracy is improved at the expense of the implementationcomplexity. The Linear Minimum Mean Square Error (LMMSE) equaliser is anexample of such an architecture (Chip-Level Channel Equalization inWCDMA Downlink, K Hooli, M Juntti, M. J. Heikkila, P. Komulainen, MLatva-aho, J. Lilleberg, EURASIP Journal on Applied Signal Processing,August 2002). The LMMSE equaliser improves the performance of thedemodulation unit by mitigating the distortions introduced by thepropagation channel. The LMMSE equaliser can be implemented using apre-filter Rake architecture (Equalization in WCDMA terminals, KariHooli, PhD thesis, 2003) where the conventional Rake receiver ispreceded by a linear filter which aims at removing the ISI introduced bythe channel.

In most propagation environments, the link level performance of thelinear equaliser will be significantly better than that of the moreconventional Rake receiver. It should however be noted that thisimprovement in performance is achieved at the expense of theimplementation complexity. This will have a negative impact on thedie-size and power-consumption of the receiver.

One of the major sources of complexity in the implementation of thereceiver comes from the large number of different operation modes thatare required. The information intended for a user may be sent over morethan one logical channel. In HSDPA for example, the information is sentover the combination of one control and one dedicated channel. Thededicated HS-DSCH channel contains the information intended for aspecific user. The HS-SCCH control channel is used to carry informationon the format of the HS-DSCH transmission. Hence, both the HS-SCCHcontrol channel and the HS-DSCH dedicated channel need to be processedat the receiver in order to recover the transmitted information. TheHS-SCCH and HS-DSCH channels are transmitted with different formats. TheHS-SCCH channel uses a spreading factor equal to 128 and is always QPSKmodulated. The spreading format of the HS-DSCH is lower and equal to 16.The proposed architecture makes it possible to efficiently receive anddemodulate the different channels processed by the receiver.

SUMMARY OF THE INVENTION

According to one aspect, the invention provides apparatus comprisingchannel estimation means for estimating a channel through which areceiver acquires a signal and Rake receiver means for operating on saidsignal, wherein the Rake receiver means is arranged to implement afinger for each tap in the channel estimate (the invention extends to acorresponding method). In this way, the invention can reduce theprocessing burden, in that it is not necessary to assess for whichchannel estimate taps Rake fingers should be allocated.

According to one aspect, the invention provides apparatus comprisingRake receiver means, pre-filter means, configuring means and evaluationmeans, wherein the pre-filter means operates on an input to the Rakereceiver means, the input represents a signal received through aphysical channel, the evaluation means is arranged to evaluate thechannel and the configuring means is arranged to re-configure thepre-filter means based on an assessment of the channel after an intervaldetermined with regard to the properties of the channel as determined bythe evaluating means (the invention also consists in a correspondingmethod). In this way, the processing burden may be adapted to the extantphysical conditions, thereby allowing unnecessary calculations to beavoided.

According to one aspect, the invention provides apparatus comprisingRake receiver means, pre-filter means and configuring means, wherein thepre-filter means operates on an input to the Rake receiver means, thepre-filter means and the Rake receiver means form the basis of an LMMSEreceiver and the configuring means is arranged to calculate filtercoefficients for use in the pre-filter means and is arranged to makethose coefficients symmetrical (the invention also extends to analogousmethods of determining filter coefficients for pre-filter meansassociated with Rake receiver means). Endowing the pre-filter stage ofan LMMSE receiver with symmetrical filter coefficients can reduce thenumber of computations involved in the operation of the pre-filterstage. Moreover, rendering the coefficients symmetrical may not besignificantly detrimental to the operation of the LMMSE receiver. Incertain embodiments, a set of filter coefficients is calculated for thepre-filter means, e.g. by reference to CIR measurements, and is thenrendered symmetric. This rendering may be achieved by averagingcalculated coefficients that appear at symmetric positions, for example.

According to one aspect, the invention provides apparatus comprisingpre-filter means and Rake receiver means, which together form the basisof an LMMSE receiver, means for determining filter coefficients for usein the pre-filter means from a signal that is provided for processingthrough the pre-filter means and the Rake receiver means and means fordelaying the signal that is provided to the pre-filter means in order toreduce time misalignment at the pre-filter means between the signal andthe coefficients (the invention also extends to a corresponding method).By reducing or—preferably—eliminating this time mis-alignment, betterperformance may be obtained from the LMMSE receiver of which thepre-filter means and the Rake receiver means are a part. In certainembodiments, the delay implemented by the delay means is variable toaccount for variation in the duration of the processing required toproduce the coefficients (e.g. variation due to variability in filteringused to refine channel estimates from which the coefficients aregenerated). In certain embodiments, the delay implemented by the delaymeans is fixed without significant detriment to the operation of theLMMSE receiver of which the pre-filter means and Rake receiver means area part.

According to one aspect, the invention provides a method of amelioratingchannel effects present in a signal received through a channel, themethod comprising assessing the interference affecting the signal andprocessing the signal to ameliorate channel effects, if intra-cellinterference dominates inter-cell interference in the signal, in amanner comprising filtering the signal through filter means toameliorate channel dispersion in the signal and then processing thesignal through Rake receiver means or, if intra-cell interference doesnot dominate inter-cell interference in the signal, in a mannercomprising processing the signal through the Rake receiver means withoutprior amelioration of channel dispersion by the filter means (theinvention extends to corresponding apparatus). In this way, theprocessing burden can be based on the techniques that are likely to havegreatest effect.

According to one aspect, the invention provides a method of quantisingsoft decisions, the method comprising determining a quantisation stepand quantising soft decisions using the step, wherein the size ofquantisation step is determined with regard to the distribution of thesoft decisions (the invention extends to the corresponding apparatus).In this way, the number of bits, or other quanta, used to represent softdecisions representing a signal can be constrained, potentially leadingto a reduction in data storage requirements. The step size may or maynot be based on the mean of a group of soft decisions. The step size maybe based on a variance or standard deviation of a group of softdecisions. Typically, the step size is driven so that it increases asthe distribution increases and decreases as the distribution decreases.

According to one aspect, the invention provides apparatus comprisingpre-filter means, Rake receiver means, channel estimation means and aphysical connection between the channel estimating means on the one handand the Rake receiver means and the pre-filter means on the other hand,wherein the channel estimating means is arranged to, when a signalwithout transmit diversity is acquired, estimate the physical channelthrough which the signal is received and is arranged to, when a signalwith transmit diversity is acquired, produce a combined channel estimatefor the physical channels through which the signal is received and theapparatus is arranged such that said connection is used for providingboth types of channel estimate to the Rake receiver means and to thepre-filter means. In this way, a saving is achieved in that theconnection is re-used. In certain embodiments, a further transmitdiversity mode is present and additional physical connections areprovided between the channel estimating means and the Rake receivermeans to convey channel estimates for the physical channels involved inthe additional transmit diversity mode.

According to another aspect, the invention provides apparatus forprocessing a communications signal that has been acquired through aphysical channel, the apparatus comprising a plurality of Rake receivermodules each arranged to process the signal under the guidance of adifferent channel estimate (the invention also consists in acorresponding method). Typically, the different channel estimates relateto different logical channels having different transmit diversitysettings (one of which may be “no transmit diversity”).

Although the present invention has been described previously in terms ofmethod and apparatus, the invention also extends to software forexecution through suitable data processing hardware to implement thesignal processing techniques of the invention.

By way of example only, certain embodiments of the invention will now bedescribed with reference to the accompanying drawings, in which:

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 presents a typical digital communication system where thepre-filter Rake architecture is used;

FIG. 2 presents an embodiment of an equalisation receiver;

FIG. 3 presents a second embodiment of an equalisation receiver;

FIG. 4 presents link-level performance results for differentover-sampling ratios;

FIG. 5 presents a possible implementation of a demapper unit; and

FIG. 6 shows physical connections between elements shown in FIGS. 2 and3.

DETAILED DESCRIPTION

FIG. 2 and FIG. 3 present two possible embodiments of an equalisationreceiver, which will shortly be described in detail.

The rate at which a receiver operates has a significant impact on bothcomplexity and power consumption. Typically, the number of operations tobe performed by the receiver will increase linearly with the samplingrate. Similarly, using a larger sampling rate calls for larger memorybuffers. Hence, in order to keep the implementation complexity as low aspossible, it is desirable for the receiver to operate with as low asampling rate as possible. However, it is well known that receiversoperating at a rate higher than symbol rate, also referred to asover-sampled architectures, are less sensitive to timing errors thansymbol-rate receivers (Digital Communications, John G. Proakis, 2^(nd)edition, McGraw-Hill International).

FIG. 4 presents the throughput performance of the pre-filter Rakereceiver in fading propagation conditions for both cases of asymbol-rate implementation (one sample per chip) and of an over-sampledimplementation (2 samples per chip). The throughput performance ispresented versus the timing delay seen by the receiver. It can be seenthat in the case of the symbol-rate receiver, the performancesignificantly varies with the timing used at the receiver. Thedifference in throughput between the best sampling point and the worstsampling point is approximately equal to 10%. This has to be contrastedagainst the performance of the over-sampled receiver where thethroughput is essentially flat against the timing delay. Hence, using anover-sampled implementation of the receiver reduces/eliminates the needfor accurate selection of the sampling point. It is important to notethat the best throughput achieved by the symbol-rate receiver is in factnot worse than the best throughput achieved by the over-sampledreceiver. Hence if the ideal sampling phase can be selected, it ispossible for the receiver to operate on the symbol-rate signal withoutany performance penalty.

Based on this observation, the first processing stage in the proposedarchitecture of FIG. 2 applies a timing correction to the receivedsignal. The timing correction filter 201 processes the received signalwhich is over-sampled and generates two output signals. It should benoted that it is typical for the over-sampling factor in the inputsignal to be equal to two. The timing correction unit 201 applies adelay to the received signal and outputs two different versions of thisdelayed signal. The first output signal is generated with a samplingrate equal to that of the input signal. This first output signal is alsodecimated, using a fixed phase, to symbol rate in order to generate thesecond output signal. Hence, the timing correction unit produces twooutput signals having different sampling rates.

The timing correction filter unit 201 can be implemented usingFractional Delay Filters (FDF) combined with a decimation stage togenerate the symbol-rate output. The application of the proposedreceiver architecture is not limited to any specific implementation ofthe FDF section. Different possible implementations can for example byfound in Principles of Fractional Delay Filters, V. Valikimaki, T. I.Laasko, IEEE International Conference on Acoustics Speech and SignalProcessing, June 2000.

The timing correction applied by unit 201 is controlled by the estimatedtiming error t derived in the timing error estimation unit 202. Thetiming error estimation unit 202 derives an estimate of the timing errorin the received signal from the over-sampled signal generated output by201. Different implementations of the timing error estimation unit arepossible.

In the embodiment presented in FIG. 2, the over-sampled signal output bythe timing correction unit 201 is only used by the timing errorestimation unit 202. Any further processing in the receiver is performedon the symbol rate signal. Hence, only the receiver front-end processingrequired to derive the optimum signal timing is performed on theover-sampled signal. By so doing, the complexity of the receiver isgreatly reduced. For example, the memory requirements associated withthe delay line 203 are much lower than those of prior-art solutionswhere the complete processing chain is operating on signals with a rateequal to that of the input signal.

In the embodiment presented in FIG. 3, the over-sampled signal at theoutput of the timing correction unit 201 is used both for timing errorestimation 202 and for channel estimation 204. This embodiment istherefore more complex than that described in FIG. 3 but is still lesscomplex than prior-art solutions. It can be seen, for example, that thememory requirements for the delay line 203 are the same for bothembodiments.

Following the timing adjustment made in 201, the receiver estimates thecharacteristics of the propagation channel in unit 204. Channelestimation can either be performed on the symbol-rate signal (FIG. 2) oron the over-sampled signal (FIG. 3). In both cases, the channelestimates produced by the channel estimation unit 204 correspond to thepropagation channel sampled at the symbol rate. Since the processingunits using the channel estimates (205 and 207) operate on thesymbol-rate version of the signal, there is no benefit in generating anover-sampled representation of the propagation environment. The channelestimation unit 204 will usually use the training sequence and/or pilotsignal that is typically embedded in the transmitted signal. In theHSDPA system for example, the Common Pilot Channel (CPICH) can be usedto estimate the propagation environment. Different techniques can beused to generate the channel estimates from this pilot signal.Typically, the channel impulse response is estimated by correlating thereceived samples with the known pilot channel symbols. A number oftechniques can then be used to refine these initial channel estimates.It is possible, for example, to filter the different channel taps inorder to reduce the power of the estimation noise. Such techniques aredescribed in “Adaptive Channel Estimation in DS-CDMA Systems”, J. W.Choi and Y. H. Lee, ECTI Transactions on Electrical Engineering,Electronics and Communications, vol. 2, no. 1, February 2004.

The channel estimation unit 204 also returns an estimate of the noisepower in the received signal. It should be noted that this estimateshould only include the power of the noise corresponding to signals thatcannot be equalised by the receiver. This can be achieved by estimatingthe combined power of the thermal noise and the inter-cell interference.Techniques making it possible to calculate the power of both intra-celland inter-cell interference are described in “Improving Channel DecoderPerformance on the CDMA Forward Link”, IEEE Transactions on WirelessCommunications, vol. 4, no. 3, May 2005.

In cellular communication systems, it is possible to useTransmit-Diversity (TxD) in order to improve the link level performance.When such a scheme is used, the transmitter sends signals from twodifferent antennas. These two signals then go through differentpropagation channels before being received and demodulated. The receiverthen needs to combine these two different signals in order to recoverthe transmitted information. In the HSDPA system, two different TxDschemes are implemented (3GPP TS 25.211—Physical channels and mapping oftransport channels onto physical channels (FDD)).

Space Time Transmit Diversity (STTD) is an open loop scheme where thetransmission format is selected without any feedback information fromthe receiver. The second diversity scheme operates in a closed-loopmanner and is referred to as CLTD.

When CLTD is used, a phasor is applied to the signal transmitted fromthe second antenna. The phasor to be applied at the transmitter isselected based on feedback from the receiver. The phase correction to beapplied to the estimates of the second propagation channel beforecombination may come from a number of different sources. The phasedifference between the signals transmitted between the two antennas maybe known a-priori. It may also be possible for the channel estimationunit 204 to produce an estimate of this phase difference from thereceived signal.

It should also be noted that different TxD schemes can be usedsimultaneously. For example, in the HSDPA system it is possible for theHS-SCCH channel to be transmitted using STTD while the HS-DSCH usesCLTD. The receiver needs to simultaneously process and demodulate thesetwo logical channels using different diversity schemes.

In order to efficiently support the reception of multiple channels withdifferent diversity formats, the channel estimation unit is designed tooutput three sets of channel estimates. As indicated before, all threesets of channel estimates correspond to the propagation channel sampledat the symbol rate.

The first set of channel estimates is provided over physical connection601 (FIG. 6) and is input to both the filter configuration unit 205 andto the first Rake processing unit 207. In the absence of TxD, this setof channel estimates correspond to the single propagation channel. WhenCLTD is used on the HS-DSCH, this output corresponds to the combinedchannel from both transmit antennas. This combined channel is derived byadding the estimates of the first-antenna channel with those of thesecond antenna after the CLTD phasor has been applied. When STTD is usedon both the HS-DSCH and HS-SCCH channels, this output of the channelestimation unit 204 is disabled.

The second and third sets of channel estimates, which are provided overphysical connections 602 and 603 respectively, are generated when STTDis used either for the HS-SCCH channel or the HS-DSCH channel. Theycorrespond to the propagation links between each of the two transmitantennas and the receiver. These channel estimates are then input to theRake processing unit. It should be noted that these channel estimatesare scaled by the inverse of the combined power of the two propagationchannels. This scaling is implemented in order to simplify the operationof the demapper 209.

In case of single link transmission, i.e. not TxD, or when CLTD is used,the first set of channel estimates are passed to the filterconfiguration unit 205. As indicated before, the channel estimation unit204 also provides an estimate of the noise power in order to derive thefilter configuration. The filter configuration unit 205 takes theinformation provided by the channel estimation unit 204 and derives thecoefficients of the filter 206.

Different implementations of the filter configuration unit 205 can beselected and their description is beyond the scope of this document. Thereader will be referred to Chip-Level Channel Equalization in WCDMADownlink, K. Hooli, M. Juntti, M. J. Heikkila, P. Komulainen, M.Latva-aho, J. Lilleberg, EURASIP Journal on Applied Signal Processing,August 2002 for a review of different possible implementations. Itshould however be noted that it is typical for the filter computationunit 205 to implement some sort of matrix inversion processing. Hence,the complexity associated with the derivation of the coefficients forthe filter 206 is usually high.

The rate at which channel estimates are generated depends on thetransmission format of the pilot channel from which these estimates arederived. In the HSDPA system, it is typical for the channel estimates tobe produced every 512 chips, equivalent to one fifth of a slot. Thefilter configuration unit 205 usually operates at the same rate as thechannel estimation unit 204. In order to reduce the computationalcomplexity of the receiver, it is possible for the filter configurationunit 205 to operate at a lower rate. It is proposed to dynamicallyselect the rate at which the filter configuration unit 205 operates. Therate adaptation can be performed based on the characteristics of thepropagation environment. In slowly changing conditions, it is notrequired to generate a new filter configuration very frequently. If thechannel varies slowly, it would, for example, be possible to generate anew filter configuration only once per slot. In fast moving conditions,the filter configuration unit 205 could operate at the maximum rate, setby that of the channel estimation process. By matching the operationrate of the filter configuration unit 205 to the channelcharacteristics, it is possible to reduce the computational complexitywithout any severe link-level performance degradation. A number ofdifferent metrics can be derived during the channel estimation processin order to estimate the rate of change in the channel environment andselect the operation rate of the filter configuration unit 205. Forexample, it is possible to estimate the Doppler frequency associatedwith the channel. It is possible to estimate the Doppler spread of thechannel by using techniques described in “A Doppler estimation forUMTS-FDD based on channel power statistics”, D. Mottier and D. Castelainin Proc. VTC 1999—Fall, pp. 3052-3056, 1999.

The coefficients calculated in unit 205 are then used to configure thefilter 206 applied to the symbol-rate signal output by the timingcorrection unit 201. It should be noted that in this document the filter206 is also referred to as pre-filter. It can be seen from FIG. 2 andFIG. 3 that the signal goes first through a delay line 203 before beingfiltered. This delay line aims at aligning the signal being filteredwith the coefficients of the filter. The generation of the channelestimates and the derivation of the filter configuration will usuallyhave delays associated with them. For example, filtering is usuallyemployed in the channel estimation unit 204. Such filtering operationwill introduce a delay in the generation of the channel estimates. Thisdelay is equal to the group delay of the filter being employed.Moreover, the generation of the filter coefficients using the channelestimates is not instantaneous. Hence, the delay introduced by theprocessing in unit 205 also needs to be taken into account. By delayingthe received signal using the delay line 203, it is possible to alignthe signal filtered in 206 with the correct tap coefficient values. Inorder to achieve a perfect correction, the delay introduced in the delayline needs to be set equal to the combined delay through the channelestimation and filter configuration units.

It should however be observed that the delay due to the channelestimation may not be fixed. As indicated previously, filtering may beperformed in the channel estimation process. Hence, the group delay ofthese filtering operations needs to be corrected for. The filter used inthe channel estimation unit 204 may not be fixed. The frequency responseof the channel estimation filter may be adapted to the propagationenvironment. When the filter configuration is varied according to therate of change of the transmission channel, the group delay is not fixedanymore. Hence, the delay introduced in the delay line 203 should alsobe dynamically modified in order to match that of the channel estimationunit 204. Such an adaptive delay scheme may be complex to implement.Moreover, for some configurations of the channel estimation filter, thedelay may be very large. When the rate of change of the channel is verylow, it is beneficial to use filters with very narrow bandwidth in orderto improve the channel quality of the channel estimates. However, whenthe bandwidth of the filter is small, the group delay will typically bevery large. This implies that the delay introduced by 203 will need tobe large and hence the associated buffer size will also be high. Whenthe delay through 203 is perfectly matched to the channel estimation andfilter configuration processes, the buffer implemented in 203 needs tobe large enough in order to cope with the maximum group delay.

However, it has been determined that it is acceptable for theconfiguration of the delay line 203 to be fixed and set to match theminimum delay through the channel estimation and filter configurationunits. Having a fixed delay greatly simplifies the implementation of thedelay line 203. Moreover by setting this fixed delay equal to theminimum processing delay, the memory requirements of the delay line aregreatly reduced. This means however that the configuration of the filter206 does not always match perfectly the signal being processed. Thiswill be true when the channel estimation group delay is larger than itsminimum value. However the channel estimation group delay usuallyincreases when the rate of change in the propagation medium becomeslower. Hence, the mismatch between the pre-filter configuration and thesignal being processed will not lead to any significant performancedegradation.

The values of the coefficients in the pre-filter control the frequencyresponse of the filter and hence the characteristics of the outputsignal. In one embodiment of the proposed receiver architecture, thecoefficients of the pre-filter are forced to be symmetrical. By doingso, the implementation complexity associated with the filteringoperation can be significantly reduced. The equation below describes ageneric filtering operation:

${y(n)} = {{\sum\limits_{k = 0}^{2 \times L}{{h(k)} \times {x\left( {n - k} \right)}}} = {\sum\limits_{k = {- L}}^{L}{{h\left( {k + L} \right)} \times {x\left( {n - k - L} \right)}}}}$x(n) and y(n) are used to denote the input and output signal samplesrespectively. The 2×L+1 filter coefficients are denoted as h(k).

When the filter coefficients are forced to be symmetrical, the followingcondition is met for the different filter coefficients:h(L+k)=h(L−k)

The filtering computations can then be re-organised in order to make useof this characteristic of the coefficients:

$\begin{matrix}{{y(n)} = {{{h(L)} \times {x\left( {n - L} \right)}} + {\sum\limits_{- L}^{- 1}{{h\left( {k + L} \right)} \times {x\left( {n - k - L} \right)}}} +}} \\{\sum\limits_{1}^{L}{{h\left( {k + L} \right)} \times {x\left( {n - k - L} \right)}}} \\{= {{{h(L)} \times {x\left( {n - L} \right)}} + {\sum\limits_{1}^{L}{{h\left( {L - k} \right)} \times {x\left( {n + k - L} \right)}}} +}} \\{\sum\limits_{1}^{L}{{h\left( {k + L} \right)} \times {x\left( {n - k - L} \right)}}} \\{= {{{h(L)} \times {x\left( {n - L} \right)}} + {\sum\limits_{1}^{L}{{h\left( {k + L} \right)} \times \left( {{x\left( {n + k - L} \right)} + {x\left( {n - k - L} \right)}} \right)}}}}\end{matrix}$

The number of multiplications required to implement a generic filteringoperation is equal to 2×L+1. When the filter coefficients are forced tobe symmetrical, the number of multiplications is equal to L+1. Hence, byforcing the coefficients of the pre-filter to be symmetrical, the numberof multiplications to be performed has almost been halved. Thisrepresents a very significant saving for the implementation of thereceiver.

Different techniques can be used to force the filter coefficients to besymmetrical. For example, it is possible to select the values for onehalf of the filter and force the other filter half to use these values.Alternatively, it would be possible for each coefficient to calculatethe average value across the two halves of the filter.

The equalisation receiver implementing an LMMSE solution will usuallyperform better than the more conventional Rake receiver. It is also morecomplex to implement as the received signal needs to be processed by thepre-filter 206. The coefficient values also need to be derived in unit205. The equaliser removes the multi-path introduced by the propagationchannel and restores the orthogonality between the different signalstransmitted under the scrambling code of the cell of interest. Hence,after de-spreading the intra-cell interference can be removed, or atleast the level of intra-cell interference can be significantly reduced.It should however be stressed that the equalisation receiver does noteliminate, nor mitigate, neither inter-cell interference nor thermalnoise. Hence, in conditions where inter-cell interference and thermalnoise dominate intra-cell interference, the performance gains providedby the equalisation receiver will be very small. In fact under suchoperating conditions, the performance of the pre-filter Rake and that ofthe Rake receiver will be very similar. Hence, when the performance ofthe pre-filter Rake is not expected to be noticeably superior to that ofthe Rake receiver, the filter configuration unit 205 and the pre-filter206 are disabled. In this configuration, the implementation of thereceiver architecture corresponds to that of a Rake receiver. By doingso, the power consumption of the receiver can be reduced without havingany significant impact on the link level performance. The switchingbetween the two receiver configurations can be based in the ratio ofintra-cell interference to inter-cell interference and noise. It shouldbe noted that when the receiver is configured to operate as a Rakereceiver, the expected delay through the pre-filter 206 could beincorporated into the delay line 203. When this is performed, the delaythrough the receiver is the same for the two different configurations.

Following filtering in 206, the signal is processed by the Rakeprocessing unit 207. The Rake processing unit also takes inputs from thedelay line 203 which are used in case of open-loop transmit diversity.The Rake processing unit is implemented as three separate Finite ImpulseResponse (FIR) filters with coefficients equal to channel estimatesderived in the channel estimation unit 204. The configuration and use ofthe three filters depends on the transmit diversity mode being used.

When transmit diversity is disabled, only one of the three filters isused. The filter coefficients are set equal to the single set of channelestimates derived in unit 204. The Rake unit 207 then processes thesamples output by the pre-filter 206.

When open-loop transmit diversity is used, two of the three filters areenabled. The filter coefficients are set equal to the two different setsof channel estimates corresponding to the transmission links from thetwo different antennas. When such a transmit diversity mode is used, theRake unit 207 processes the samples at the output of the delay line 203.

When closed-loop transmit diversity is used, all three filters in 207are enabled and running. In such a configuration, the HS-DSCH channel istransmitted with CLTD whereas the HS-SCCH channel, which needs to besimultaneously received, is transmitted using STTD encoding. Hence, theRake unit 207 needs to process the received signal for both transmitdiversity modes. The first filter is therefore configured using thechannel estimates corresponding to the combination of the twotransmission links. Note that as indicated before when describing theoperation of the channel estimation unit, the combination of the twosets of channel estimates is performed using the knowledge of, or anestimate of, the phase shift applied at the transmitter. This first Rakefilter processes the samples generated by the pre-filter unit 206 and isused to receive the HS-DSCH channel. The second and third filters areused to receive the HS-SCCH channel. They are configured using thechannel estimates corresponding to the individual transmission linksfrom the two antennas. They process samples directly from the output ofthe delay line 203.

It should be noted that the proposed implementation of the Rakeprocessing unit 207 is slightly different to that of prior-artsolutions. It is typical for the Rake receiver to allocate fingers toonly a sub-set of the estimated channel taps. In the implementationdescribed in this document, the contributions from all the channel tapsare taken into consideration. Such an approach presents two mainadvantages. First, since all the contributions from the propagationchannel are used to generate the samples output by the Rake processingunit 207, the accuracy of the demodulation process can be improved.Moreover there is no need for any complicated logic to select thechannel taps to which Rake fingers should be allocated. This, however,needs to be balanced against the increase in the effective number offingers.

Following processing by the Rake unit 207, the I/Q samples are input tothe de-spreader 208. The de-spreader simply correlates the input samplesagainst the combined spreading and scrambling code for each of thephysical channels to be received. For each physical channel, a singleoutput sample is generated when the correlation has been calculated overthe spreading factor of the given channel. Different strategies can beselected for the implementation of the correlation processing. Anefficient architecture in the case of multi-code reception can be foundin ‘Low Power Strategy About Correlator Array for CDMA BasebandProcessor’, C. W. Ku, F. Y. Kuo, C. K. Chen and L. G. Chen, IEEEWorkshop on Signal Processing Systems, 1999. SiPS 99. 1999.

It should also be noted that when open-loop transmit diversity is used,either for the HS-SCCH only or for both HS-SCCH and HS-DSCH channels,the de-spreader 208 also performs the STTD decoding.

The de-spreading unit 208 generates a series of I/Q samples for eachphysical channel to be received. These I/Q samples then need to bedemodulated in order to generate soft decisions to be passed to theerror-correction decoding unit 107. The processing to be performeddepends on the modulation format used by the transmitter and isimplemented in unit 209. The implementation of the demapper unit 209 ispresented in FIG. 5. The different processing steps presented in FIG. 5need to be repeated for each physical channel being received.

From the received signal, the average amplitude λ and the average powerχ are first estimated. Note that this estimation is performed over ablock of received samples. In the preferred embodiment of the proposedinvention, these estimates are generated using samples corresponding toa fifth of a slot. The estimated average amplitude λ is then used toconfigure the constellation demapping unit 302 which processes thereceived signal. The implementation of the constellation demapping unit302 depends on the modulation schemes being used by the transmitter. Thesoft decisions generated by the constellation demapping unit 302 arethen input to the quantiser 303. The aim of the quantiser is to reducethe number of bits used to represent the soft decisions passed to theerror-correction decoding unit 107.

Unit 303 uses both the average amplitude λ and the quantisation step Ξto configure the quantisation process of the soft decisions. Thequantisation step Ξ is derived in unit 304 from both the averageconstellation amplitude λ and the average constellation power χ:Ξ=f(λ,χ)

Where f is designed to increase the quantisation step size when thedistribution of amplitude values increases and to decrease thequantisation step size when the distribution of amplitude valuesdecreases.f(λ,χ)=λ+√{square root over (χ−λ²)}

In order to reduce the implementation complexity of the proposeddemapping approach, it is possible to delay the application of theestimates λ and χ. For example, these estimates could be derived fromsamples corresponding to a specific fifth of a slot and then be appliedto the samples corresponding to the next fifth of a slot. By so doing,the processing can be performed ‘on the fly’ without requiring anybuffering. When such an approach is used, it is necessary to providesome initial estimates of the λ and χ quantities. It would for examplebe possible to use values derived from a-priori knowledge.Alternatively, it would be possible to use the last set of estimates tohave been generated in order to initialise the next set of values.

In on embodiment of the proposed invention, it is possible to reduce theimplementation complexity by sharing some of the processing functionsacross multiple physical channels. For example, when multiple physicalchannels are transmitted with the same power, it is possible to produceestimates for the λ and χ quantities using samples from only one of thephysical channels. This single set of estimates can then be appliedacross all the physical channels using the same transmit powerconfiguration. In HSDPA for example, it is possible to estimate the λand χ quantities only once for all the HS-DSCH channels.

1. A method of ameliorating channel effects present in a signal receivedthrough a channel, the method comprising assessing the interferenceaffecting the signal and processing the signal to ameliorate channeleffects, if intra-cell interference dominates inter-cell interference inthe signal, in a manner comprising filtering the signal through filtermeans to ameliorate channel dispersion in the signal and then processingthe signal through Rake receiver means or, if intra-cell interferencedoes not dominate inter-cell interference in the signal, in a mannercomprising processing the signal through the Rake receiver means withoutprior amelioration of channel dispersion by the filter means.
 2. Themethod according to claim 1, wherein the step of assessing theinterference comprises calculating the ratio of, on the one hand,intracell interference and, on the other hand, intercell interferenceand noise.
 3. A method of quantising soft decisions, the methodcomprising determining a quantisation step and using the step toquantise soft decisions obtained by demodulating symbols constituting asignal, wherein the size of the quantisation step is determined withregard to an amplitude distribution of the symbols, wherein saiddetermining step comprises characterising said distribution using afunction of the average amplitude of and of the average power of symbolsfrom the signal.
 4. The method according to claim 3, wherein saidfunction has the form λ+√{square root over (χ−λ²)}, wherein λ is theaverage amplitude and χ is average constellation power.